Abstract
Asian rust affects the physiology of soybean plants and causes losses in yield. Repeatability coefficients may help breeders to know how many measurements are needed to obtain a suitable reliability for a target trait. Therefore, the objectives of this study were to determine the repeatability coefficients of 14 traits in soybean plants inoculated with Phakopsora pachyrhizi and to establish the minimum number of measurements needed to predict the breeding value with high accuracy. Experiments were performed in a 3x2 factorial arrangement with three treatments and two inoculations in a random block design. Repeatability coefficients, coefficients of determination and number of measurements needed to obtain a certain reliability were estimated using ANOVA, principal component analysis based on the covariance matrix and the correlation matrix, structural analysis and mixed model. It was observed that the principal component analysis based on the covariance matrix out-performed other methods for almost all traits. Significant differences were observed for all traits except internal CO2 concentration for the treatment effects. For the measurement effects, all traits were significantly different. In addition, significant differences were found for all Treatment x Measurement interaction traits except coumestrol, chitinase and chlorophyll content. Six measurements were suitable to obtain a coefficient of determination higher than 0.7 for all traits based on principal component analysis. The information obtained from this research will help breeders and physiologists determine exactly how many measurements are needed to evaluate each trait in soybean plants infected by P. pachyrhizi with a desirable reliability.
Highlights
Soybean (Glycine Max (L.) Merrill) is one of the most important cereal crops worldwide
The objectives of this study were: (i) to determine the repeatability coefficients of the 14 traits evaluated in soybean plants inoculated with P. pachyrhizi; and (ii) to establish, based on the coefficient of repeatability and determination, the minimum number of measurements needed to predict the breeding value for each trait
Climate conditions during the experiment are displayed in S1 Fig. The genotype BRS 361 was used in this study as a susceptible control to Asian Rust Soybean (SBR)
Summary
Soybean (Glycine Max (L.) Merrill) is one of the most important cereal crops worldwide. World production reached 312 million tons in the 2015/2016 season harvested from 119 million hectares [2]. Brazil is the second worldwide soybean producer behind the United States, with a production in the 2015/2016 season reaching 95 million tons harvested from 33 million hectares [3]. The worldwide soybean production is high, the yield is not suitable (2.62 tons ha-1). A disease that stands out, mainly in South America, is Asian soybean rust (SBR). This disease is caused by the fungal pathogen Phakopsora pachyrhizi. In Brazil, this disease has caused more than R$40 billion in crop losses since it was first detected in 2001 [4, 5]. Three strategies have been used to control SBR: applying chemical fungicides, employing specific cultivation practices, and most recently breeding or engineering of SBR-resistant soybean cultivars [8,9,10]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
